Standard transcriptomic analyses cannot fully capture the molecular mechanisms underlying disease pathophysiology and outcomes

Researchers at Cincinnati Children’s Hospital Medical Center present a computational heterogeneous data integration and mining protocol that combines transcriptional signatures from multiple model systems, protein-protein interactions, single-cell RNA-seq markers, and phenotype-genotype associations to identify functional feature complexes. These feature modules represent a higher order multifeatured machines collectively working toward common pathophysiological goals. The researchers apply this protocol for functional characterization of COVID-19, but it could be applied to many other diseases.

Ghandikota S, Sharma M, Jegga AG. (2021) Computational workflow for functional characterization of COVID-19 through secondary data analysis. STAR Protoc 2(4):100873. [article]

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